Résumé
Master the fundamentals of SPSS with this newly updated and instructive resource
The newly and thoroughly revised Second Edition of SPSS Essentials delivers a comprehensive guide for students in the social sciences who wish to learn how to use the Statistical Package for the Social Sciences (SPSS) for the effective collection, management, and analysis of data. The accomplished researchers and authors provide readers with the practical nuts and bolts of SPSS usage and data entry, with a particular emphasis on managing and manipulating data.
The book offers an introduction to SPSS, how to navigate it, and a discussion of how to understand the data the reader is working with. It also covers inferential statistics, including topics like hypothesis testing, one-sample Z-testing, T-testing, ANOVAs, correlations, and regression. Five unique appendices round out the text, providing readers with discussions of dealing with real-world data, troubleshooting, advanced data manipulations, and new workbook activities.
SPSS Essentials offers a wide variety of features, including:
A revised chapter order, designed to match the pacing and content of typical undergraduate statistics classes
An explanation of when particular inferential statistics are appropriate for use, given the nature of the data being worked with
Additional material on understanding your data sample, including discussions of SPSS output and how to find the most relevant information
A companion website offering additional problem sets, complete with answers
Perfect for undergraduate students of the social sciences who are just getting started with SPSS, SPSS Essentials also belongs on the bookshelves of advanced placement high school students and practitioners in social science who want to brush up on the fundamentals of this powerful and flexible software package.SECTION I - INTRODUCTION
Chapter 1: What is SPSS
1) Introduction
2) What is SPSS used for
3) The power of SPSS
4) SPSS compared to other programs
Chapter 2: Navigating SPSS
1) How the program works
a) Data files
b) Syntax files
c) Output files
2) Managing your SPSS life through folders
a) Importance of maintaining raw data
Chapter 3: Introduction to Data
1) Understanding your data
a) Independent Versus Dependent Variables
b) Scales of Measurement
2) The SPSS Data Perspective
a. Data represented by numbers
b. Data represented by words
c. The other variable types
3) Your Data in SPSS (Matrices)
Chapter 4 Getting Your Data into SPSS
1) Before SPSS
2) Specifying Operations through SPSS
3) Creating a Data Shell
a) Creating Data Files Via Syntax
4) Numeric Versus String Variables
5) Data Entry Within the Syntax File
6) "Saving" Populated Data Files
a) Controlling your open data files
Chapter 5: Accessing Your Data
1) Accessing Your Data Files
a) Get File and Save Outfile
b) Creating Subsets of Data
2) Importing Data from Excel
a) Using the Import Wizard
b) Copy-Paste Option
Chapter 6: Defining Your Data
1) Annotation
2) Defining Your Dataset
a) Adding Variable Labels
b) Adding Value Labels
SECTION II - STATISTICS
Chapter 7: Descriptive Statistics
1) Frequencies
2) Displaying Data Graphically
a) Location and Spread
3) Descriptive Statistics
a) Measures of Central Tendency and Variability
4) General Note on Analyses
5) General Note on Output Files
Chapter 8: Hypothesis Testing
1) Descriptive vs. Inferential Statistics
2) Hypothesis Testing (A Process for Interpreting Inferential Statistics)
a) Six Steps of Hypothesis Testing
Chapter 9: Inferential Analyses (z - and t-tests)
1) One Sample z-test
2) The t-test
a) One Sample t - test
b) Two Independent Samples t - test
c) Two Correlated/Paired Samples t - test
Chapter 10: Inferential Analyses (ANOVAS)
1) One-Way ANOVA
2) Repeated Measures ANOVA
3) Factorial ANOVA
4) Follow-up Contrasts
Chapter 11: Inferential Analyses (Correlation and Regression)
1) Correlation
2) Simple Regression
3) Multiple Regression
a) Straight Regression
b) Hierarchical Regression
4) Visualizing your Relationship
Chapter 12: Inferential Analyses (Nonparametrics)
1) Parametric vs. Nonparametric analyses
2) Chi-square
a) Two variable chi-square examples
SECTION III - ADVANCED DATA MANAGEMENT
Chapter 13: Manipulating Your Data
1) SPSS's Intended purposes
a) Data analyst
b) Data organizer
2) Creating Scale Scores
a) Recoding your data
b) Creating your scales
3) The Importance of Selecting All
Chapter 14: Collapsing and Merging Data Files
1) Same people, different information
2) Different people, same information
Chapter 15: Differential treatment of your data
1) Isolating interesting cases
a) Creating a new data file
b) Splitting files
2) Summary
Chapter 16: Using your Output
1) Problem solving
a) Spaces in all the wrong places
b) Column information
c) There is one little thing...
2) Maximizing output information
Chapter 17: Other tricks of the trade
1) Salvaging Old Syntax
a) The Importance of Notepad
2) Tricking SPSS to "Think" Across Rows
a) Transposing Your Matrix
b) Aggregating Your Files
3) "Do If" and "End If"
Appendixes
Appendix A: Completed Questionnaire Form example
Appendix B: Example Code Sheet for Questionnaire
Appendix C: Summary of Creating and Defining a Data File
Appendix D: Example Syntax File Integrating Multiple Commands
Answers to Chapter Discussion Questions
IndexJOHN T. KULAS, PhD, is a Professor of Industrial and Organizational Psychology at Montclair State University in Montclair, NJ, United States.
RENATA GARCIA PRIETO PALACIOS ROJI, MA, is a PhD candidate in Industrial and Organizational Psychology at Montclair State University in Montclair, NJ, United States.
ADAM M. SMITH, PhD, is an associate consultant at Kincentric and adjunct instructor at Wentworth Institute of Technology and Harvard University.
